Press release

The Connected States of America -- Using mobile communications to redraw community boundaries.

CAMBRIDGE, Mass. -- Researchers at MIT Senseable City Lab, AT&T
Labs-Research and IBM Research are revealing new research that
redefines regional boundaries in the United States, using patterns of
social connectedness across the country derived from anonymous and
aggregated cell phone data.

In some cases, connectedness follows traditional demarcations such as
state lines -- but in other cases, new patterns are emerging that have
little to do with political or administrative boundaries. By looking
at billions of instances of aggregated[*] mobile communication, researchers
are able to define communities through the more informal lens of
social networks.

"This work proposes a novel, fine-grained approach to understanding
cities and human communities in space," says Carlo Ratti, director of
the MIT Senseable City Lab.

Cities play an important role in defining community boundaries, as
they tend to pull nearby counties into their radius of influence. This
radius of influence depends on factors such as size, population
density and geography of the city’s surroundings. The researchers
explain cities' radius of influence in terms of laws similar to
Newton's laws of gravitation: Larger places attract more people and
businesses than smaller ones, and the attraction between closer places
is greater than that between remote ones. As a first approximation,
the likelihood of two people communicating with one another depends on
the respective populations of the origin and destination of the call,
and drops off according to the distance between them.

The "Connected States of America" provides a more natural delineation
of regions that follows relationships between family, friends and
business partners. However, "telecom and state partitionings of the US
results are very similar, as 90% of counties in the official state
partitioning fall within a corresponding (by largest overlap) telecom
community" - comments Francesco Calabrese, advisory research staff
member at IBM Research-Ireland. "Sister states" emerge, such as
Georgia and Alabama, Mississippi and Louisiana, and Tennessee and
Kentucky, among others. Metropolitan areas often form pockets of
influence that extend into neighboring states or communities; for
example, Chattanooga, Tenn., is more closely linked to communities in
Georgia and Alabama than to the rest of Tennessee. Pittsburgh, Penn.,
and West Virginia form a new "state," while St. Louis, Mo., exhibits
an expanded reach that splits Illinois into two regions. New Jersey
and California also divide into two distinct regions due to large
cities. In contrast, Texas remains whole: Despite the potentially
splitting influence of cities such as Dallas, Houston, San Antonio and
Austin, the researchers found that there is enough inter-city
communication to hold the state together.

However, a simple gravitational model does not explain all of the
results. For example, distance between places can be measured in
several ways: as the crow flies, along transportation routes or by
travel time. Mountain ranges and other geographic features influence
how people interact, because they contribute to an increased
perception of distance and therefore hinder communication. "This
phenomenon may explain, for example, why Chattanooga appears cut off
from the rest of Tennessee and better connected to parts of Georgia
and Alabama," says Dominik Dahlem, a postdoc at the Senseable City
Lab.

Interestingly, analyzing boundaries according to aggregate and
anonymous records of text messages (SMS) instead of phone calls yields
a different map of connectedness. Some sister-state pairings change —
for example, instead of Georgia-Alabama and Louisiana-Mississippi, SMS
data link Mississippi and Alabama, leaving Louisiana and Georgia as
stand-alone states. Oklahoma and Arkansas break apart, while West
Virginia and Ohio join together. California splits into three
communities instead of two. According to the researchers, these
differences can be explained by the fact that SMS is generally favored
by a younger population and is less likely to reflect
cross-generational communication. Also, the SMS map is more divided
overall, indicating that people are less likely to send text messages
over large distances than they are to make phone calls.

This data reveals patterns of social and economic activity that the
researchers expect will be of interest to social scientists and
policymakers. "We are particularly interested in how such rich
information can help us gain a better understanding of our society,
which in the future, could lead to more democratic, bottom-up
structures of governance," Ratti says.

"This example illustrates once again the insights that can be inferred
from aggregated communication patterns, as wells as how collaboration
across fields of research can benefit for society," said Alexandre
Gerber, a researcher at AT&T Labs.

Analogous results for Great Britain were recently published by the
same team in the journal PLoS ONE, which analyzed 12 billion
anonymized records representing more than 95 percent of Great
Britain's residential and business landlines. In that study,
communities that emerge out of people's communication habits were
found to be more cohesive than administrative boundaries.

The research was done in partnership with AT&T Labs-Research, IBM
Research and the National Building Museum in Washington. Support was
generously granted by the Rockefeller Foundation, the National Science
Foundation, the AT&T Foundation, the MIT SMART program, GE, Audi
Volkswagen, SNCF and the members of the MIT Senseable City Lab
Consortium. For visualizations and more background information, please
visit http://senseable.mit.edu/csa.

[*] All communication data was aggregated
by county, determined by the caller's and recipient’s most frequently
used cell tower, which was assumed to be near their residence. In
order to determine which counties are connected most closely by
communications, researchers analyzed anonymized location data for both
ends of the calls and texts. No personal information was used.